Data is often encoded into a different form to facilitate for example communication, storage or identification. An example of encoding data is to reduce a quantity of data to be communicated or stored in some way. Such encoding is also known by the term compression or compression encoding. Whilst compression encoding is applicable to all types of data, data compression finds particular application with video data, because typically video data which represents images requires a relatively large quantity of data in order to represent the images.
Known encoding techniques for video data use the Discrete Fourier Transform or the Discrete Cosine Transform (DCT) to convert the image data from the spatial domain to a transform domain in which the image pixel values are de-correlated. The de-correlated transform domain data may then be more efficiently compression encoded. Moreover, in the transform domain, the DCT coefficients which represent the DCT encoded image can be quantised, thereby reducing an amount of data required to represent the image. Furthermore, when the image is Inverse Discrete Cosine Transform decoded, a reduction in the image quality as the decoded image appears to the human eye is usually so small as to be not noticeable, particularly if the higher frequency components are quantised to a greater extent than the lower frequency components. For example, the DCT transform is used in the Joint Photographic Experts Group (JPEG) and the Motion Picture Experts Group (MPEG) II compression encoding standards.
Although the DCT transform has been widely adopted, in particular for compression encoding, the DCT transform suffers a disadvantage because typically a length of binary data words which are used to represent the DCT coefficients is greater than the length of the data in the spatial domain. As a result, a significant amount of quantisation must be performed, discarding information, from the encoded image, before a compression gain is effected. Furthermore at high compression ratios (encoded data compared to un-coded data quantity), a significant loss of image quantity is caused, when the quantised DCT encoded image is inverse quantised and IDCT decoded.